UNASSIGNED: Cyclic thrombocytopenia (CTP) is a rare blood disorder characterized by periodic fluctuations in platelet counts. CTP usually appears in pre-menopausal women, and these fluctuations of platelets are in phase with the menstrual cycle. CTP is a heterogeneous disease, and the pathogenic mechanism is still unclear. Therefore, it harbors great significance for exploring the association of fluctuations in platelet counts with hormonal-cycle.
UNASSIGNED: Firstly, we washed human platelets from healthy volunteers following the Declaration of Helsinki. Flow cytometer was employed to measure the mitochondrial inner transmembrane potential (ΔΨm) depolarization, PS exposure, P-selectin expression, and GPIIb/IIIa activation in platelets. In addition, western blot detected the related protein expression. The corresponding assay kit measured the caspase-3 and PDE3A activity. Finally, flow cytometry determined mouse platelets labeled with calcein.
UNASSIGNED: We find a reverse relationship between the platelet count and serum estradiol (E2) level in a CTP patient. We demonstrated that E2 induces platelet apoptosis in vitro and platelet clearance in vivo. We further discovered that E2 activates phosphodiesterase 3A, which inhibits protein kinase A (PKA), leading to PKA-mediated platelet apoptosis. Activation of PKA protected platelets from E2-induced thrombocytopenia and elevated the number of mice circulatory platelets.
UNASSIGNED: We find that E2 induces platelet apoptosis and clearance through PDE3A-mediated PKA inhibition. Activation of PKA rescues E2-induced thrombocytopenia in mice. Thus, our study reveals a pathogenesis of E2-related CTP and suggests promising therapeutic strategies for the disease.

BACKGROUND: Increased urinary free cortisol in response to the oral administration of dexamethasone is a paradoxical reaction mainly reported in patients with primary pigmented nodular adrenocortical disease. Here, we describe the first case of subclinical Cushing\'s syndrome represented by autonomous cortisol secretion and paradoxical response to oral dexamethasone administration, harboring an activating mutation in the α subunit of the stimulatory G protein (GNAS).
METHODS: A 65-year-old woman was diagnosed with subclinical Cushing\'s syndrome during an evaluation for bilateral adrenal masses. Tumors of unknown origin were found in the heart, brain, thyroid gland, colon, pancreas, and both adrenal glands. Adenocarcinoma of the sigmoid colon and systemic brown-patchy skin pigmentation were also present. Her urinary cortisol levels increased in response to oral dexamethasone, while serum dehydroepiandrosterone-sulfate was not suppressed. After right adrenalectomy, genetic analysis of the resected tumor revealed the somatic GNAS activating mutation, p.R201H. Paradoxical urinary cortisol response persisted even after unilateral adrenal resection, although serum and urinary cortisol levels were attenuated.
CONCLUSIONS: This patient harbored a GNAS activating mutation, and presented with a mild cortisol- and androgen-producing adrenal adenoma. Administration of oral dexamethasone paradoxically increased cortisol levels, possibly via the stimulation of the cyclic adenosine monophosphate-dependent protein kinase A signaling pathway, which is seen in patients with pigmented nodular adrenocortical disease or Carney complex. GNAS mutations may provide clues to the mechanisms of hyper-function and tumorigenesis in the adrenal cortex, especially in bilateral adrenal masses accompanied by multiple systemic tumors. Examining GNAS mutations could help physicians detect extra-adrenal malignancies, which may contribute to an improved prognosis for patients with this type of Cushing\'s syndrome.

The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.